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Title:	應用情感分析於股票趨勢預測 -以台灣人工智慧(AI)概念股為例 Sentiment Analysis in Taiwan Artificial Intelligence Concept Stock
Authors:	曾梓閑 Tseng, Zi-Xian
Contributors:	姜國輝季延平 Jiang, Guo Hui Chi, Yan Ping 曾梓閑 Tseng, Zi-Xian
Keywords:	情感分析文字探勘機器學習時間序列分析人工智慧概念股
Date:	2018
Issue Date:	2018-07-13 15:16:47 (UTC+8)
Abstract:	近年來人工智慧的發展及應用備受各界關注，隨著人工智慧發展大躍進，AI概念股在這波浪潮下因運而生，而2017年AI類股相關指數漲贏美股大盤，人工智慧發展對我國也帶來了重要的影響，本研究中對台灣人工智慧概念股做一個初步的調查，並依據技術面與應用面定義出29支台灣AI概念股作為本研究之研究範圍。本研究利用財經新聞作為情感分析的來源，計算出情緒指數後利用時間序列分析找出與情緒指數相關的指標，再建立分類模型來預測股票的漲跌。經實證結果發現，情緒指數與人工智慧概念股股價走勢有其影響，推測散戶看到新聞報導後會受到新聞文本的影響進而影響股價走勢，並於2~3 天影響最為明顯。另外，本研究實驗結果中也發現結合情緒指數與技術指標建立的分類模型優於單純以技術指標分類模型來預測股價的漲跌趨勢。而加入其他間接指標如國際指標、總體經濟指標、台股資訊指標建立的分類模型優於結合情緒指數與技術指標建立的分類模型，整體分類準確度達82%。在結合情緒指數與技術指標的分類模型上，以分類器的準確度及召回率效果而言，KNN的準確率為0.8 及召回率為0.67的分類結果較為優異，以F1-measure而言則是0.65 的隨機森林效果較為優異。
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Description:	碩士國立政治大學資訊管理學系 1053560163
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G1053560163
Data Type:	thesis
DOI:	10.6814/THE.NCCU.MIS.003.2018.A05
Appears in Collections:	[Department of MIS] Theses

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